As electronic commerce and electronic inventory systems become more wide spread, new difficulties arise in regards to providing and ensuring the accuracy of product information. For example, in an electronic inventory, each separate product includes many different attributes. The attributes may include identifying numbers, prices, brand names, detailed descriptions and so on. Accordingly, ensuring the information is accurate when an individual category of the inventory may include thousands of separate products is a complex and time consuming task especially considering entering the information is a manual process.
For example, in the context of a grocery store, each product entered into the electronic inventory may include many different attributes such as weight, flavor, brand name, price, pieces per package and so on. The various attributes generally correlate with separate columns in a database and, thus, the information is manually reviewed and entered into the separate columns by workers. Furthermore, because the product descriptions are unstructured and do not follow any particular format, they may include grammatical errors, spelling errors, and/or other errors. Accordingly, simply copying the information into the database does not provide accurate and properly catalogued information. Thus, providing accurate product descriptions in a database is a difficult task with many complexities.